A striker who shoots at his own goal. A midfielder who shares your game plan with the opponent. A player who burns through the entire season's budget in one match.

These aren't hypotheticals—these are AI agents in production.

As the manager of your AI squad, you've assembled talented players that can search, reason, and execute complex plays. But without proper coaching, discipline, and testing, they go rogue. How do you build a championship-caliber team you can trust?

In this session, I'll introduce AgentEval—the .NET evaluation toolkit I built to bring testing discipline to AI agents. Think of it as your coaching staff, analytics team, and referee all in one.

You'll learn to:
- Validate formations: Did your agents execute the play in the right order?
- Enforce team rules: Forbidden moves, required approvals, compliance policies
- Scout consistently: Handle AI unpredictability with statistical confidence
- Track performance: Set standards that bench agents who exceed budget or miss SLAs

Through code demos, you'll see agent tests pass and fail—with feedback that actually helps you improve your squad. Whether you're building customer service agents, automation workflows, or enterprise AI, you'll leave ready to coach a reliable team.

Your agents will follow tactics. Guaranteed.